Stearoyl-CoA desaturase-1 is vital for milk lipid synthesis: Deletion impairs mammary gland and neonatal development
Bibliographic record
Abstract
The mammary gland synthesizes and secretes nutrient-rich milk containing lactose, protein, and lipids, with the complex assortment of lipids providing more than half of the energy and bioactive factors that impact the growth and development of neonates. The birth of neonates initiates the lipogenic capacity of the mammary gland with upregulation in expression of lipogenic genes, including Stearoyl-CoA desaturase (Scd1). SCD1 plays a critical role in lipogenesis, catalyzing the conversion of saturated fatty acids to monounsaturated fatty acids. Previous studies of Scd1 knockout mice revealed that SCD1 impacts several metabolic processes in the liver and adipose tissue, including fat synthesis. However, the role of SCD1 in lactation is not fully understood. Our study aimed to determine the role of SCD1 in lactation and the effects of maternal knockout of Scd1 on the growth of the lactating neonates. We employed second-parity Scd1-deficient female mice (n = 7) that we compared with wild-type mice (n = 6). To determine lipid and metabolic alterations, mammary gland and milk samples were harvested on lactation day 10. Relative to wild-type mice, mammary gland weight, alveolar area, and milk glycerolipid content were reduced in lactating Scd1-deficient mice. Scd1 deficiency also diminished mammary gland biosynthetic metabolic pathways, such as glycerolipid and phospholipid synthesis, while enhancing catabolic pathways, such as fatty acid oxidation. Neonates nursed by Scd1-deficient mice exhibited lower body weights. These findings highlight the critical role of SCD1 in orchestrating metabolic adaptations during lactation to ensure adequate milk synthesis to support the rapidly growing neonates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".